Marketing Opportunity
Video-call glitches trigger uncanniness and harm consequential life outcomes
Melanie Brucks, Jacqueline Rifkin & Jeff Johnson
Nature, forthcoming
Abstract:
People are increasingly using video calls for high-stakes interactions that once required face-to-face contact: from medical consultations, to job interviews, to court proceedings. But video calling introduces a new communication issue: minor glitches, or intermittent errors in the transmission of audiovisual information during a virtual interaction. Here, through five experiments and three supplementary studies using both live and recorded interactions, we show that minor audiovisual glitches during video calls harm interpersonal judgements in consequential life domains (for example, hiring decisions after a virtual interview, or trust in a medical provider after a telehealth visit). In addition, two archival datasets from real-world video calls reveal that glitches are associated with both reduced social connection and a lower likelihood of being granted criminal parole. We find that audiovisual glitches damage interpersonal judgements because they break the illusion of face-to-face contact (for example, by distorting faces, misaligning audio and visual cues or making movements appear 'choppy'), evoking 'uncanniness' — a strange, creepy or eerie feeling. As the uncanniness of a glitch increases, so does its negative effect on interpersonal judgements. Furthermore, audiovisual glitches undermine interpersonal judgements only in video calls that simulate face-to-face interaction, showing that the negative effect produced by glitches goes beyond mere disruptiveness, comprehension difficulties and negative attributions. These findings have important implications for digital equity. Despite being considered a boon to access, virtual communication might unintentionally perpetuate inequality. Because disadvantaged groups often have poorer internet connections, they are likely to encounter more glitches, and, in turn, to experience worse outcomes in consequential contexts such as health, careers, justice and social connection.
Leveraging AI to Evaluate Commercial Success: Application to TV vs. Digital Ads
Jin Ho Yun et al.
University of Pennsylvania Working Paper, September 2025
Abstract:
This work examines the empirical viability of a novel approach to appraising the comparative effectiveness of traditional TV versus social media digital advertising. The approach develops a fusion deep learning model that integrates electroencephalography (EEG) data — neurophysiological activity collected as consumers view advertisements — with audiovisual embeddings extracted from the ad itself. This model generates an EEG-Video (EV) score, a contextual-temporal metric measuring neural engagement to specific elements of ad content. The authors then link these individual-level EV scores to population-level ad preference and econometric-level, ad carryover elasticities derived from time-series data on stock price responses to ad spending. Across 173 participants randomly assigned to either TV or digital conditions, the authors find that ads shown in TV contexts elicit not only greater EV scores but stronger neural responses than those viewed on digital platforms. Importantly, only the EV metric significantly predicts aggregate ad preference as well as ad carryover elasticities from the TV condition, over and beyond ad recall and conventional EEG metrics. The new approach offers a scalable, interpretable, and practically generalizable metric for optimizing commercial responses and media strategy, advancing both consumer neuroscience and marketing analytics.
Forecasted vs. Actual Generosity in Image-Concern Interventions
Minah Jung et al.
Management Science, forthcoming
Abstract:
Prior research and lay intuition suggest that amplifying image concerns promotes generosity. We test the impact of image-based interventions in consumer elective pricing (CEP), where individuals choose how much to pay for products or services. Across 10 studies (nine field experiments and one laboratory study, n = 3,182), we examine the effects of these interventions on payments and elicit forecasts from independent participants (n = 1,636). Forecasters predict large positive effects, yet behavioral data reveal small and inconsistent impacts. What drives the inconsistency between predictions and actual outcomes? Studies with more than 4,000 forecasters show that neither simulating the decision-making experience nor prior experience with CEP improve prediction accuracy. However, avoiding direct comparisons between experimental conditions — which can artificially amplify perceived differences — reduces overestimation. These findings highlight challenges associated with transferring behavioral insights across contexts and show how forecast elicitation methods shape expectations of intervention effectiveness.
The Impact of Melodic Repetition
Giovanni Luca Cascio Rizzo & Jonah Berger
University of Pennsylvania Working Paper, September 2025
Abstract:
Music is often used in ads, stores, and social media posts, and consumers frequently consume music as part of their daily lives. But why does certain music have a bigger impact on consumer behavior? A multimethod investigation, combining automated audio analysis of thousands of songs using cutting-edge audio processing algorithms with controlled experiments using music in ads, demonstrates the role of melodic repetition: music that repeats the melody more often is evaluated more positively, performs better (i.e., ranks higher on the Billboard charts), and boosts responses towards products advertised with it. Further, the studies illustrate that this effect is driven by processing ease. Melodic repetition makes music easier to process, which boosts response. Taken together, these findings shed light on the effect of musical features, why some music is more impactful, and how automated audio analysis can be used to provide insight into consumer behavior.
Open Devices and Slices: Evidence From Wi-Fi Equipment
Do Yoon Kim, Roberto Fontana & Shane Greenstein
NBER Working Paper, December 2025
Abstract:
The study examines the quasi-natural experiments provided by the staggered introduction of open drivers in the supply chains for routers. It is rare to observe components become open and measure whether openness generates a statistical impact on more products and innovative products. This study collects novel data on all routers and subcomponents introduced between 2000 and 2018, characterizing each firm's position in a supply chain as either an upstream component provider or a downstream router assembler. Following prior literature, openness influences a firm's ability to negotiate with current and potential partners, which is labeled as autonomy. Evidence suggests that openness enhances supplier autonomy, increases the introduction of new products, and leads to a greater number of products located closer to the technical frontier. These estimates suggest that openness increased product introductions by enlarging the options available to component suppliers. The largest component suppliers benefited from greater sales, and no evidence indicates that openness aided entrants, small firms, or assemblers.